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- # Copyright 2022 Meta Platforms, Inc. and The HuggingFace Inc. team. All rights reserved.
- #
- # Licensed under the Apache License, Version 2.0 (the "License");
- # you may not use this file except in compliance with the License.
- # You may obtain a copy of the License at
- #
- # http://www.apache.org/licenses/LICENSE-2.0
- #
- # Unless required by applicable law or agreed to in writing, software
- # distributed under the License is distributed on an "AS IS" BASIS,
- # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- # See the License for the specific language governing permissions and
- # limitations under the License.
- """RegNet model configuration"""
- from huggingface_hub.dataclasses import strict
- from ...configuration_utils import PreTrainedConfig
- from ...utils import auto_docstring
- @auto_docstring(checkpoint="facebook/regnet-y-040")
- @strict
- class RegNetConfig(PreTrainedConfig):
- r"""
- groups_width (`int`, *optional*, defaults to 64):
- Width of group for each stage.
- layer_type (`str`, *optional*, defaults to `"y"`):
- The layer to use, it can be either `"x" or `"y"`. An `x` layer is a ResNet's BottleNeck layer with
- `reduction` fixed to `1`. While a `y` layer is a `x` but with squeeze and excitation. Please refer to the
- paper for a detailed explanation of how these layers were constructed.
- downsample_in_first_stage (`bool`, *optional*, defaults to `False`):
- If `True`, the first stage will downsample the inputs using a `stride` of 2.
- Example:
- ```python
- >>> from transformers import RegNetConfig, RegNetModel
- >>> # Initializing a RegNet regnet-y-40 style configuration
- >>> configuration = RegNetConfig()
- >>> # Initializing a model from the regnet-y-40 style configuration
- >>> model = RegNetModel(configuration)
- >>> # Accessing the model configuration
- >>> configuration = model.config
- ```
- """
- model_type = "regnet"
- layer_types = ["x", "y"]
- num_channels: int = 3
- embedding_size: int = 32
- hidden_sizes: list[int] | tuple[int, ...] = (128, 192, 512, 1088)
- depths: list[int] | tuple[int, ...] = (2, 6, 12, 2)
- groups_width: int = 64
- layer_type: str = "y"
- hidden_act: str = "relu"
- downsample_in_first_stage: bool = True
- def validate_architecture(self):
- """Part of `@strict`-powered validation. Validates the architecture of the config."""
- if self.layer_type not in self.layer_types:
- raise ValueError(f"layer_type={self.layer_type} is not one of {','.join(self.layer_types)}")
- __all__ = ["RegNetConfig"]
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